quantitative critique
Nairobis81
QuantitativeArticle_NairobisVarela.pdf
Geriatric Critical Care
©2021 American Association of Critical-Care Nurses doi:https://doi.org/10.4037/ajcc2021221
Background Sleep duration and proportion of daytime versus nighttime sleep may affect cognitive function in older patients in the transition out of the intensive care unit. Objective To explore the relationship between the daytime-to-nighttime sleep ratio and cognitive impairment in older intensive care unit survivors. Methods The study enrolled 30 older adults within 24 to 48 hours after intensive care unit discharge. All partici- pants were functionally independent before admission and underwent mechanical ventilation in the intensive care unit. Actigraphy was used to estimate daytime (6 am to 9:59 pm) and nighttime (10 pm to 5:59 am) total sleep duration. Daytime-to-nighttime sleep ratios were calcu- lated by dividing the proportion of daytime sleep by the proportion of nighttime sleep. The National Institutes of Health Toolbox Cognition Battery Dimensional Change Card Sort Test (DCCST) was used to assess cognition. Associations between sleep and cognition were explored using multivariate regression after adjusting for covariates. Results The mean (SD) daytime sleep duration was 7.55 (4.30) hours (range, 0.16-14.21 hours), and the mean (SD) nighttime sleep duration was 4.99 (1.95) hours (range, 0.36-7.21 hours). The mean (SD) daytime-to-nighttime sleep ratio was 0.71 (0.30) (range, 0.03-1.10). Greater daytime sleep duration (β = −0.351, P = .008) and higher daytime-to-nighttime sleep ratios (β = −0.373, P = .008) were negatively associated with DCCST scores. Conclusions The daytime-to-nighttime sleep ratio was abnormally high in the study population, revealing an altered sleep/wake cycle. Higher daytime-to-nighttime sleep ratios were associated with worse cognition, sug- gesting that proportionally greater daytime sleep may predict cognitive impairment. (American Journal of Critical Care. 2021;30:e40-e47)
Daytime-to-Nighttime Sleep RatioS aND CogNitive impaiRmeNt iN olDeR iNteNSive CaRe UNit SURvivoRS By Maya N. Elías, PhD, RN, Cindy L. Munro, PhD, ANP-BC, and Zhan Liang, PhD, RN
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Geriatric Critical Care
Cognitive impairment and sleep disturbances are prevalent among older ICU survivors.
E ven more than 1 year after critical illness, about 25% of adult intensive care unit (ICU) survivors experience post-ICU cognitive impairment comparable in severity to that of mild Alzheimer disease, and about 33% have cognitive impairment compara- ble to that associated with moderate traumatic brain injury.1 Critically ill older adults, especially those who have undergone mechanical ventilation, are at highest risk for
post-ICU cognitive impairment.2
Older adults require adequate sleep throughout recovery from critical illness.3 Altered sleep distribu- tion throughout the 24-hour sleep/wake cycle is com- mon in ICU patients: more than 50% of total sleep time in the ICU occurs during the daytime,4 and such sleep is highly fragmented, particularly among patients receiving mechanical ventilation.5 The extent to which these sleep alterations persist after ICU and hospital discharge remains largely unknown.
Post-ICU cognitive impairment is a component of post-ICU syndrome,6 which contributes to geriatric syndromes. At the time of hospital discharge, up to 90% of older ICU survivors have at least 1 geriatric syndrome,7 which may include cognitive decline.8,9 Significant advancements in critical care have improved mortality rates among hospitalized older ICU survivors. In fact, adults aged 65 and older who have undergone mechanical ventilation during their ICU stay are now more likely to survive until hospital discharge, but with greater comorbidity and disability.10
Pre-ICU or premorbid risk factors for post-ICU cognitive impairment may include age; sex; medical, neurological, or psychiatric history; preexisting cog- nitive impairment; apolipoprotein E genotype, and/ or drug and alcohol abuse.11 Intensive care unit– related risk factors for post-ICU cognitive impairment may include mechanical ventilation, sedation and analgesic use, hypotension and hypoxemia, glucose dysregulation, sepsis, acute renal failure, neurologi- cal dysfunction, and metabolic abnormalities.12,13 Many of these pre-ICU and ICU-related risk factors for post-ICU cognitive impairment also overlap with risk factors for post-ICU sleep alterations (ie, mechani- cal ventilation, sedation and analgesic use, cardiovas- cular and respiratory medications, sepsis and infection, stress and anxiety, preexisting illnesses, and severity
of illness).4,14 Post-ICU cognitive impairment15 and sleep disturbances16,17 are prevalent among ICU sur- vivors even after hospital discharge.
To our knowledge, researchers have not yet examined the association between objective mea- sures of sleep and cognitive impairment in hospital- ized older ICU survivors who received mechanical ventilation while in the ICU. Rather, research on sleep (using objective measures, such as actigraphy or polysomnography) and cognition in older adults has focused on relatively healthy, community-dwelling older adults18-23 or older adults discharged from an inpatient postacute rehabilitation facility.24
The aims of the present study were (1) to examine the relationship between sleep duration and cogni- tive impairment, (2) to calculate the daytime-to- nighttime sleep ratio in study participants, and (3) to explore the relationship between this daytime-to- nighttime sleep ratio and cognitive impairment in hospitalized older ICU survivors. We hypothesized that, because sleep alter- ations contribute to cogni- tive decline even in healthy aging,25,26 this relationship may be exacerbated by critical illness, with a higher post-ICU daytime-to- nighttime sleep ratio being negatively associated with cognitive impairment.
Methods Study Design and Ethical Considerations
This small, exploratory study used a cross-sectional design. The study was approved by the university institutional review boards, and all participants provided written informed consent in English before enrollment, per the study protocol.
Sample and Setting
We enrolled 30 English-speaking hospitalized older ICU survivors (aged ≥65 years) who were func- tionally independent before hospital admission, had no preexisting diagnosis of dementia, and required mechanical ventilation (≥12 hours) while in the ICU.
About the Authors Maya N. Elías is a postdoctoral research fellow, Cindy L. Munro is dean and a professor, and Zhan Liang is an assistant professor, School of Nursing and Health Studies, University of Miami, Coral Gables, Florida.
Corresponding author: Maya N. Elías, PhD, RN, 5030 Brunson Dr, Ste 423, Coral Gables, FL 33146 (email: [email protected]).
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We then calculated the “daytime-to-
nighttime sleep ratio” by dividing the propor-
tion of daytime sleep by the proportion of
nighttime sleep.
We recruited patients from all 12 medical-surgical floors of a level I trauma hospital, regardless of admis- sion diagnosis or type of ICU, within 24 to 48 hours after ICU discharge. Participants were selected through convenience sampling between November 2017 and January 2018. The time window of within 24 to 48 hours of transfer out of the ICU was chosen to cap- ture the early post-ICU period.
To be included in the study, participants had to be previously community-dwelling adults (ie, admit- ted from home) aged 65 years or older and able to speak English to provide informed consent and par- ticipate in data collection. In addition, participants had to have been functionally independent before hospital admission. The Katz Index of Independence in Activities of Daily Living, a subjective measure of physical function, was used to assess the participant’s baseline functional ability (ie, before hospital admis- sion) to independently perform 6 activities of daily living: bathing, dressing, toileting, transferring, con-
tinence, and feeding.27 The Katz Index has demonstrated high reliability, with Cron- bach α coefficients ranging from 0.87 to 0.94.28 Potential participants who scored less than 6 on the Katz Index (range, 0-6, with 6 indicating func- tional independence without any supervision or assistance required) were deemed ineli- gible for the study. Participants were asked to retrospectively
comment on their baseline ability to perform each of these activities of daily living independently 2 weeks before hospital admission.29 Exclusion crite- ria were imminent death, active palliative care or
hospice orders, and history or suspicion of preexist- ing dementia on medical record review.
Measures and Procedures The variables and measures included in our
analyses, as well as data collection time points, are summarized in Figure 1.
Sleep Duration. Wrist actigraphy (Actiwatch Spectrum [Philips]) was used to collect data on total daytime sleep duration and nighttime sleep duration consecutively throughout a 2-night/1-day observation period, beginning at the time of study enrollment. Actigraphy has been used to measure sleep/rest versus activity in hospitalized patients,30-32 in ICU patients,33 and among ICU survivors after hospital discharge.16 Acceleration counts were col- lected in 15-second epochs. We defined “daytime sleep duration” as the duration of sleep between 6 am and 9:59 pm during 1 daytime observation period. We defined “nighttime sleep duration” as the mean duration of sleep of the 2 consecutive nighttime periods between 10 pm and 5:59 am. We then defined “24-hour sleep duration” as the sum of daytime sleep duration and the mean nighttime sleep duration for analyses. Daytime and nighttime hours were chosen on the basis of unit routines at the hospital site; for example, on most units, checks of vital signs were typically scheduled for 6 am, 10 am, 2 pm, 6 pm, 10 pm, and 2 am.
Daytime-to-Nighttime Sleep Ratio. Sleep efficiency was defined as the sleep duration divided by the total number of hours spent in bed.33 We analyzed daytime sleep efficiency (between 6 am and 9:59 pm, for a single 16-hour daytime period) and nighttime sleep efficiency (between 10 pm and 5:59 am, averaged over 2 consecutive 8-hour nighttime periods) using wrist actigraphy. We then calculated the “daytime- to-nighttime sleep ratio” by dividing the proportion of daytime sleep by the proportion of nighttime sleep. As an example, a healthy older adult who does not sleep or nap during the 16-hour daytime period but sleeps for 6 out of the 8 hours during the nighttime period would have a ratio of 0 ([0/16]/[6/8]) (Figure 2).
Cognition/Executive Function. The National Insti- tutes of Health (NIH) Toolbox Cognition Battery36 Dimensional Change Card Sort Test (DCCST) was used to assess cognitive flexibility. Cognitive flexibil- ity is a subdomain of executive function. Specifically, cognitive flexibility is the set-shifting component of executive function and consists of the ability to shift responses based on rules or contingencies. The first author (M.N.E.), who attended a live 2-day training
Prospective data collection:
Post-ICU
• Daytime sleep (actigraphy)
• Nighttime sleep (actigraphy)
• Daytime-to-nighttime sleep ratio (actigraphy)
• Cognitive flexibility (DCCST)
• Grip strength (GST)
Retrospective data collection:
Pre-ICU and ICU
• Demographic characteristics (age, sex)
• History of obstructive sleep apnea (medical record review)
• Baseline sleep quality (PSQI)
• ICU severity of illness (APACHE III)
Figure 1 Key variables and data collection time points. Abbreviations: APACHE, Acute Physiology and Chronic Health Evaluation; DCCST, National Institutes of Health Toolbox Cognition Battery Dimensional Change Card Sort Test; GST, National Institutes of Health Toolbox Motor Battery Grip Strength Test; ICU, intensive care unit; PSQI, Pittsburgh Sleep Quality Index.
Transfer out of ICU
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workshop on the NIH Toolbox measures, administered all 30 DCCST assessments. The DCCST assessments were completed on the day after the participant’s enrollment in the study, during the daytime (ie, the second day of sleep observation). Assessments were completed at the bedside: before conducting the DCCST, the researcher approached the assigned nurse and requested an “appointment” for an unin- terrupted period of about 5 to 10 minutes to com- plete the assessment. The DCCST has demonstrated good reliability (intraclass correlation coefficients ranging from 0.82 to 0.92) and good construct validity (convergent validity coefficient of −0.52).36,37 Fully corrected T scores (adjusted for age, sex, race/ ethnicity, and level of education; range, 0-100) on the DCCST were used for analyses.
Covariates. Age, sex, history of obstructive sleep apnea (OSA), and severity of illness score on ICU admission (Acute Physiology and Chronic Health Evaluation [APACHE] III38) were collected via medi- cal record review. We assessed baseline sleep quality before hospital admission using the Pittsburgh Sleep Quality Index (PSQI).39 The PSQI holds internal consistency, demonstrates high reliability (Cronbach α = 0.83) for its 7 components, and has been vali- dated in both older men40 and older women.41 Par- ticipants answered questions on the PSQI at the time of enrollment on the basis of how they slept at home, and higher PSQI global scores indicated worse sleep quality (range, 0-21). We assessed grip strength at time of enrollment using the NIH Tool- box Motor Battery Grip Strength Test (GST)42 of handgrip dynamometry, because motor impairment is a component of post-ICU syndrome,6 and the GST fully corrected T score was used for analyses. The test-retest reliability of grip strength measured by the GST was good to excellent (intraclass correla- tion coefficients ranging from 0.88 to 0.98).42
Statistical Analyses Data were analyzed with IBM SPSS Statistics,
version 26. Pearson correlation coefficients were used to examine bivariate correlations; covariates with correlation coefficients less than 0.20 were con- sidered for inclusion in the models. Exploratory multivariate regression models were used to exam- ine the cross-sectional associations between the independent variables (total daytime sleep duration, mean nighttime sleep duration, 24-hour sleep dura- tion, and daytime-to-nighttime sleep ratio) and the dependent variable (fully corrected T score on the DCCST), after adjusting for the selected covariates. Model 1 adjusted for age, sex, history of OSA, and
PSQI. Model 2 adjusted for age, sex, history of OSA, PSQI, APACHE III, and GST.
Results Sample Characteristics
A total of 26 participants with complete data on all aforementioned measures were included in the final analyses. One participant was transferred back to the ICU after only 1 night of actigraphy, and 3 participants did not fully complete the DCCST. Of the 26 participants, the mean (SD) age was 70.62 (4.77) years, 10 (38%) were female, and 22 (85%) identified as White and non-Hispanic/Latino. On average, participants spent 5.43 (7.89) days receiving mechanical ventilation while in the ICU; the mean ICU length of stay was 12.46 (12.14) days. The mean APACHE III score was 96.19 (29.47) (range, 50-157),
Daytime hours: 6 am-9:59 pm Daytime sleep
Nighttime hours: 10 pm-5:59 am Nighttime sleep
Figure 2 Example of typical proportions of daytime versus nighttime sleep for a healthy community-dwelling older adult. Healthy, active, community-dwelling older adults typically do not experience sleep disturbances34—rather, they sleep primar- ily during nighttime hours, and thus should not need to nap during the daytime because of excessive daytime sleepiness.35 Therefore, their ratio of daytime sleep to nighttime sleep should be zero.
Midnight
6 am 6 pm
10 pm
Noon
Proportion of daytime sleep: 0% Daytime sleep duration: 0 hours
Proportion of nighttime sleep: 75-88% Nighttime sleep duration: 6-7 hours
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the mean PSQI score was 6.5 (2.7) (range, 1-12), and 15 participants (58%) had preexisting OSA. The mean fully corrected T score on the GST was 34.04 (13.31) (range, 5-59). A total of 12 participants (46%) received care in the medical ICU, 9 (35%) in the cardiovascular ICU, 2 (8%) in the surgical/ trauma ICU, 2 (8%) in the surgical/transplant ICU, and 1 (4%) in the neurological/neurosurgical ICU.
Descriptive Analyses of Cognition and Sleep The mean (SD) DCCST fully corrected T score
was 38.81 (9.2) (range, 24-64), which is greater than 1 SD below the normative population DCCST scores of healthy, community-dwelling older adults.
Participants’ mean (SD) nighttime sleep dura- tion was 4.99 (1.95) hours (range, 0.36-7.21 hours) between the hours of 10 pm and 5:59 am, whereas the mean daytime sleep duration was 7.55 (4.30)
hours (range, 0.16-14.21 hours) between the hours of 6 am and 9:59 pm. The mean 24-hour sleep duration was 12.48 (5.93) hours (range, 0.53- 20.77 hours).
The mean (SD) daytime-to-nighttime sleep ratio was 0.71 (0.30) (range, 0.03-1.10). The ratios for 5 (19% ) participants were greater than 1, indicating that these participants slept proportionally more during the day than at night. An example of the proportion of daytime versus nighttime sleep over a 24-hour period in these older ICU survivors is shown in Figure 3.
Exploratory Regression Models Exploratory regression models revealed that
greater daytime-to-nighttime sleep ratios were nega- tively associated with cognitive flexibility. All explor- atory regression models are detailed in the Table.
Association Between Daytime Sleep and Cognition. The regression model (Model 1) exploring the rela- tionship between daytime sleep duration and cog- nitive flexibility showed a statistically significant association (R2 = 0.748, P < .001). Greater daytime sleep duration was negatively associated with DCCST scores (β = −0.351, P = .008) after adjusting for covari- ates. The unique variance for daytime sleep duration was 11.6%: greater daytime sleep duration was sig- nificantly associated with worse cognitive flexi- bility. An additional regression model with added covariates (Model 2) also supported this negative association between daytime sleep duration and cognitive flexibility.
Association Between Daytime-to-Nighttime Sleep Ratio and Cognition. The regression model (Model 1) explor- ing the relationship between the daytime-to-nighttime sleep ratio and cognitive flexibility also indicated a sta- tistically significant association (R2 = 0.750, P < .001). Higher daytime-to-nighttime sleep ratios were nega- tively associated with DCCST scores (β = −0.373, P = .008) after adjustment for covariates. The unique variance for daytime-to-nighttime sleep ratio was 12.2%: higher daytime-to-nighttime sleep ratios were significantly associated with worse cognitive flexibility. An additional regression model with added covariates (Model 2) also supported this negative association between daytime-to-nighttime sleep ratios and cognitive flexibility.
Discussion Our study revealed that greater post-ICU day-
time sleep duration was significantly associated with cognitive impairment, specifically in terms of cogni- tive flexibility, despite transition of care out of the
Midnight
6 am 6 pm
10 pm
Noon
Daytime hours: 6 am-9:59 pm Daytime sleep
Nighttime hours: 10 pm-5:59 am Nighttime sleep
Figure 3 Example of the proportions of daytime versus night- time sleep among older intensive care unit survivors in the study sample. This figure also reflects the care routines of the hospital setting, for example, unit routines for measuring vital signs (6 am, 10 am, 2 pm, 6 pm, 10 pm, 2 am) and scheduled meal- times (6:45 am, 11 am, 4:30 pm).
Mean proportion of daytime sleep: 47.19% Mean daytime sleep duration: 7.55 hours
Mean proportion of nighttime sleep: 62.38% Mean nighttime sleep duration: 4.99 hours
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Alterations of the sleep/ wake cycle (ie, altered distribution of sleep between nighttime and daytime hours to favor greater daytime sleep) might exacerbate post- ICU cognitive impairment among older ICU survivors.
ICU. Moreover, the daytime-to-nighttime sleep ratio was abnormally high, indicating severe alterations of the sleep-wake cycle, with a proportionally large amount of post-ICU sleep occurring during the day. Alterations in the sleep-wake cycle are significantly influenced by aging; these changes can contribute to cognitive decline even in cases of healthy aging25 and may be exacerbated by sudden critical illness. A healthy and active older adult typically does not experience sleep disturbances,34 sleeping primarily during nighttime hours with short sleep latency and high sleep efficiency, and therefore should not need to nap during the daytime because of exces- sive daytime sleepiness (Figure 2).35
We found significant associations between greater daytime sleep duration and post-ICU cognitive impair- ment in a cohort of older ICU survivors. Other stud- ies examining objectively measured sleep and cognition in older adults have focused on relatively healthy, community-dwelling older adults18-23 or older adults discharged from an inpatient postacute rehabilita- tion facility.24 Excessive daytime sleepiness has also been shown to be linked to cognitive decline in community-dwelling elderly people.43 Yet these populations are not as clinically complex as our sample of older ICU survivors. Moreover, most of these studies did not report on a ratio of daytime- to-nighttime sleep or its possible link to cognition. One study (of community-dwelling older women) indicated an increased risk of cognitive impairment among older women who napped more than 2 hours daily.20 Another study suggested that lower
daytime sleep duration was associated with improvements in cognitive function among older men discharged from a Veterans Administration– affiliated, postacute rehabilitation facility.24 The findings from these 2 studies particularly support the present study of hospitalized older ICU survi- vors, in which a higher daytime-to-nighttime sleep ratio was associated with worse executive function.
Our results suggest that a greater quantity of sleep may not necessarily translate to a better quality of sleep even after discharge from the ICU. There may be an “optimal dose” of sleep duration, and both short and long sleep durations may be associ- ated with worse cognitive performance across subdo- mains of executive func- tion among healthy, community-dwelling older adults.44,45 Moreover, our results reveal that the sleep/wake cycle remains altered beyond ICU dis- charge and may still favor greater proportions of day- time sleep during hospital- ization. Thus, we suggest that alterations of the sleep/wake cycle (ie, altered distribution of sleep between nighttime and daytime hours to favor greater daytime sleep) might exacerbate post-ICU cognitive impairment among
Sleep predictor variable
Table Associations between sleep and cognitive flexibility (DCCST)
Daytime sleepd
Nighttime sleepe
24-hour sleepf
Daytime-to- nighttime sleep ratiog
Abbreviations: β, standardized coefficients; DCCST, National Institutes of Health Toolbox Cognition Battery Dimensional Change Card Sort Test fully corrected T score (outcome variable for all associations with sleep predictor variables); R2, regression coefficient of determination. a
Model 1: adjusted for age, sex, history of obstructive sleep apnea, and Pittsburgh Sleep Quality Index global score. b
Model 2: adjusted for age, sex, history of obstructive sleep apnea, Pittsburgh Sleep Quality Index global score, Acute Physiology and Chronic Health Evaluation III score, and National Institutes of Health Toolbox Motor Battery Grip Strength Test fully corrected T score.
c Significant at the P < .05 level.
d Daytime sleep: sleep duration in hours between 6 am and 9:59 pm.
e Nighttime sleep: sleep duration in hours between 10 pm and 5:59 am, averaged over 2 consecutive nights.
f 24-hour sleep: sum of daytime sleep duration and nighttime sleep duration.
g Daytime-to-nighttime sleep ratio: proportion of daytime sleep divided by proportion of nighttime sleep.
.04
.34
.08
.02
.008
.22
.02
.008
−0.286 (−1.214 to −0.035)
−0.144 (−2.149 to 0.788)
−0.245 (−0.835 to 0.058)
−0.322 (−18.276 to −1.83)
−0.351 (−1.309 to −0.222)
−0.181 (−2.259 to 0.554)
−0.308 (−0.905 to −0.070)
−0.373 (−19.907 to −3.391)
<.001
.001
<.001
<.001
<.001
.001
<.001
<.001
0.779; F7,17 = 8.545
0.697; F7,18 = 5.905
0.761; F7,17 = 7.734
0.799; F7,16 = 9.084
0.748; F5,19 = 11.263
0.639; F5,20 = 7.069
0.720; F5,19 = 9.780
0.750; F5,18 = 10.825
P cP c ββ (95% CI)ββ (95% CI)
Model 1a Model 2b
P cP c R 2; FR 2; F
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older ICU survivors. Additional research is needed to clarify these relationships between sleep and cogni- tion in ICU survivors.
Study Limitations One limitation of this study is the lack of a pre-
ICU cognitive assessment or baseline self-report, although participants with preexisting or suspected dementia were excluded from enrollment. Pre-ICU cognitive status may provide prognostic information about the likelihood of older adults maintaining independence after a critical illness.46 Per our study protocol, we collected data (retrospective medical record review) at the time of study enrollment regard- ing documentation of ICU delirium by a provider (ie, physician, psychiatrist, nurse practitioner, or reg- istered nurse). However, clinical documentation of ICU delirium in elderly ICU patients has been noto- riously unreliable for use in research studies47,48 and thus was not included as a covariate in our analyses. Actigraphy uses accelerometry and thus may over- estimate sleep duration and sleep efficiency, yet actigraphy has been well validated compared with polysomnography.49 The ease and low cost of its use renders actigraphy a feasible option, instead of poly- somnography, for any study protocols designed to evaluate sleep in the ICU and beyond the ICU.33 Finally, although our sample size was very modest, the preliminary results from these actigraphy data informed the design of a more robust, longitudinal cohort study using portable polysomnography (NIH award number F32NR018585) to examine post-ICU sleep and cognition.
Conclusion Post-ICU cognitive impairment is part of post-ICU
syndrome, and among older ICU survivors, altered sleep may be a considerable risk factor for the devel- opment of cognitive impairment.6 Older adult ICU survivors experience long-term impairments in cog- nition that persist beyond the ICU and throughout transitions of care.50,51 Executive function scores of people who survive critical illness are reported to be significantly lower than the population mean,1 which our results also support. Executive function is a prerequisite for higher cognitive capacity and functional status among older adults.52 Poor execu- tive function is independently associated with insti- tutionalization (discharge to a skilled nursing facility or long-term acute/subacute care) at hospital dis- charge.53-55 Less than 25% of older adults who receive mechanical ventilation during hospitalization are discharged home.56 In contrast, more than half of
older ICU survivors who receive mechanical ven- tilation are discharged to a skilled nursing facility.10 Sleep promotion should continue after ICU dis- charge, as sleep may be crucial for older adults’ recovery beyond the ICU; thus, health care pro- viders in post-ICU units should promote daytime activity and mobility while attempting to optimize nighttime sleep.57 Ultimately, we propose that improving post-ICU sleep may help prevent or mitigate post-ICU cognitive decline and thus may reduce symptom burden and health care costs among older ICU survivors.
FINANCIAL DISCLOSURES None reported.
REFERENCES 1. Pandharipande PP, Girard TD, Jackson JC, et al. Long-term
cognitive impairment after critical illness. N Engl J Med. 2013;369(14):1306-1316.
2. Carson SS, Cox CE, Holmes GM, Howard A, Carey TS. The changing epidemiology of mechanical ventilation: a population-based study. J Intensive Care Med. 2006;21(3): 173-182.
3. Pisani MA, Friese RS, Gehlbach BK, Schwab RJ, Weinhouse GL, Jones SF. Sleep in the intensive care unit. Am J Respir Crit Care Med. 2015;191(7):731-738.
4. Freedman NS, Gazendam J, Levan L, Pack AI, Schwab RJ. Abnormal sleep/wake cycles and the effect of environmen- tal noise on sleep disruption in the intensive care unit. Am J Respir Crit Care Med. 2001;163(2):451-457.
5. Parthasarathy S, Tobin M. Sleep in the intensive care unit. Intensive Care Med. 2004;30(2):197-206.
6. Elliott D, Davidson JE, Harvey MA, et al. Exploring the scope of post–intensive care syndrome therapy and care: engage- ment of non–critical care providers and survivors in a second stakeholders meeting. Crit Care Med. 2014;42(12): 2518-2526.
7. Tang HJ, Tang HYJ, Hu FW, Chen CH. Changes of geriatric syndromes in older adults survived from intensive care unit. Geriatr Nurs. 2016;38(2017):219-224.
8. Inouye SK, Studenski S, Tinetti ME, Kuchel GA. Geriatric syn- dromes: clinical, research and policy implications of a core geriatric concept. J Am Geriatr Soc. 2007;55(5):780-791.
9. Sacanella E, Pérez-Castejón JM, Nicolás JM, et al. Functional status and quality of life 12 months after discharge from a medical ICU in healthy elderly patients: a prospective obser- vational study. Crit Care. 2011;15(2):R105. doi:10.1186/cc10121
10. Wunsch H, Guerra C, Barnato AE, Angus DC, Li G, Linde- Zwirble WT. Three-year outcomes for Medicare beneficia- ries who survive intensive care. JAMA. 2010;303(9):849-856.
11. Hopkins RO, Jackson JC. Long-term neurocognitive function after critical illness. Chest. 2006;130(3):869-878.
12. Girard TD, Thompson JL, Pandharipande PP, et al. Clinical phenotypes of delirium during critical illness and severity of subsequent long-term cognitive impairment: a prospec- tive cohort study. Lancet Respir Med. 2018;6(3):213-222.
13. Sakusic A, O’Horo JC, Dziadzko M, et al. Potentially modifi- able risk factors for long-term cognitive impairment after critical illness: a systematic review. Mayo Clin Proc. 2018; 93(1):68-82.
14. Pulak LM, Jensen L. Sleep in the intensive care unit: a review. J Intensive Care Med. 2016;31(1):14-23.
15. Brück E, Schandl A, Bottai M, Sackey P. The impact of sepsis, delirium, and psychological distress on self-rated cognitive function in ICU survivors—a prospective cohort study. J Intensive Care. 2018;6:2. doi:10.1186/s40560-017-0272-6
16. Solverson KJ, Easton PA, Doig CJ. Assessment of sleep qual- ity post-hospital discharge in survivors of critical illness. Respir Med. 2016;114:97-102.
17. Altman MT, Knauert MP, Pisani MA. Sleep disturbance after hospitalization and critical illness: a systematic review. Ann Am Thorac Soc. 2017;14(9):1457-1468.
www.ajcconline.org AJCC AMERICAN JOURNAL OF CRITICAL CARE, March 2021, Volume 30, No. 2 e47
18. Biddle DJ, Naismith SL, Griffiths KM, Christensen H, Hickie IB, Glozier NS. Associations of objective and subjective sleep disturbance with cognitive function in older men with comor- bid depression and insomnia. Sleep Health. 2017;3(3): 178-183.
19. Blackwell T, Yaffe K, Ancoli-Israel S, et al. Associations between sleep architecture and sleep-disordered breathing and cog- nition in older community-dwelling men: the Osteoporotic Fractures in Men Sleep Study. J Am Geriatr Soc. 2011;59(12): 2217-2225.
20. Blackwell T, Yaffe K, Ancoli-Israel S, et al. Poor sleep is associ- ated with impaired cognitive function in older women: the study of osteoporotic fractures. J Gerontol A Biol Sci Med Sci. 2006;61(4):405-410.
21. Blackwell T, Yaffe K, Laffan A, et al. Associations of objectively and subjectively measured sleep quality with subsequent cognitive decline in older community-dwelling men: the MrOS sleep study. Sleep. 2014;37(4):655-663.
22. Djonlagic I, Aeschbach D, Harrison SL, et al. Associations between quantitative sleep EEG and subsequent cognitive decline in older women. J Sleep Res. 2019;28(3):e12666. doi:10.1111/jsr.12666
23. Spira AP, Stone KL, Redline S, et al. Actigraphic sleep dura- tion and fragmentation in older women: associations with performance across cognitive domains. Sleep. 2017; 40(8):zsx073. doi:10.1093/sleep/zsx073
24. Dzierzewski JM, Fung CH, Jouldjian S, Alessi CA, Irwin MR, Martin JL. Decrease in daytime sleeping is associated with improvement in cognition after hospital discharge in older adults. J Am Geriatr Soc. 2014;62(1):47-53.
25. Kondratova AA, Kondratov RV. The circadian clock and pathol- ogy of the ageing brain. Nat Rev Neurosci. 2012;13(5): 325-335.
26. Pace-Schott EF, Spencer RMC. Age-related changes in the cognitive function of sleep. Progr Brain Res. 2011;191:75-89.
27. Katz S, Ford AB, Moskowitz RW, Jackson BA, Jaffe MW. The index of ADL: a standardized measure of biological and psychosocial function. JAMA. 1963;185(12):914-919.
28. Wallace M, Shelkey M. Monitoring functional status in hos- pitalized older adults. Am J Nurs. 2008;108(4):64-71.
29. Covinsky KE, Palmer RM, Counsell SR, Pine ZM, Walter LC, Chren MM. Functional status before hospitalization in acutely ill older adults: validity and clinical importance of retrospec- tive reports. J Am Geriatr Soc. 2000;48(2):164-169.
30. Yoder JC, Staisiunas PG, Meltzer DO, Knutson KL, Arora VM. Noise and sleep among adult medical inpatients: far from a quiet night. Arch Intern Med. 2012;172(1):68-70.
31. Vinzio S, Ruellan A, Perrin AE, Schlienger JL, Goichot B. Acti- graphic assessment of the circadian rest–activity rhythm in elderly patients hospitalized in an acute care unit. Psychia- try Clin Neurosci. 2003;57(1):53-58.
32. Aibel K, Meyerhoff R, Harpole D, Abernethy AP, Yang CFJ. Sleep quality among inpatients with acute myeloid leuke- mia. J Clin Oncol. 2016;34(29):82.
33. Schwab KE, Ronish B, Needham DM, To AQ, Martin JL, Kam- dar BB. Actigraphy to evaluate sleep in the intensive care unit: a systematic review. Ann Am Thorac Soc. 2018; 15(9):1075-1082.
34. Foley D, Ancoli-Israel S, Britz P, Walsh J. Sleep disturbances and chronic disease in older adults: results of the 2003 National Sleep Foundation Sleep in America Survey. J Psychosom Res. 2004;56(5):497-502.
35. Ficca G, Axelsson J, Mollicone DJ, Muto V, Vitiello MV. Naps, cognition and performance. Sleep Med Rev. 2010; 14(4): 249-258.
36. Weintraub S, Dikmen SS, Heaton RK, et al. Cognition assess- ment using the NIH Toolbox. Neurology. 2013;80(11 suppl 3): S54-S64.
37. Zelazo PD, Anderson JE, Richler J, et al. NIH Toolbox Cognition Battery (CB): validation of executive function measures in adults. J Int Neuropsychol Soc. 2014;20(6):620-629.
38. Knaus WA, Wagner DP, Draper EA, et al. The APACHE III prog- nostic system: risk prediction of hospital mortality for criti- cally ill hospitalized adults. Chest. 1991;100(6):1619-1636.
39. Buysse DJ, Reynolds CF III, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatr Res. 1989; 28(2):193-213.
40. Spira AP, Beaudreau SA, Stone KL, et al. Reliability and valid- ity of the Pittsburgh Sleep Quality Index and the Epworth
Sleepiness Scale in older men. J Gerontol A Biol Sci Med Sci. 2012;67(4):433-439.
41. Beaudreau SA, Spira AP, Stewart A, et al. Validation of the Pittsburgh Sleep Quality Index and the Epworth Sleepiness Scale in older black and white women. Sleep Med. 2012; 13(1):36-42.
42. Reuben DB, Magasi S, McCreath HE, et al. Motor assessment using the NIH Toolbox. Neurology. 2013;80(11 suppl 3):S65-S75.
43. Jaussent I, Bouyer J, Ancelin ML, et al. Excessive sleepiness is predictive of cognitive decline in the elderly. Sleep. 2012; 35(9):1201-1207.
44. Devore EE, Grodstein F, Schernhammer ES. Sleep duration in relation to cognitive function among older adults: a system- atic review of observational studies. Neuroepidemiology. 2016;46(1):57-78.
45. Lo JC, Groeger JA, Cheng GH, Dijk DJ, Chee MWL. Self- reported sleep duration and cognitive performance in older adults: a systematic review and meta-analysis. Sleep Med. 2016;17:87-98.
46. Ferrante LE, Murphy TE, Gahbauer EA, Leo-Summers LS, Pisani MA, Gill TM. Pre-intensive care unit cognitive status, subsequent disability, and new nursing home admission among critically ill older adults. Ann Am Thorac Soc. 2018; 15(5):622-629.
47. Numan T, van den Boogaard M, Kamper AM, Rood PJT, Peelen LM, Slooter AJC. Recognition of delirium in postop- erative elderly patients: a multicenter study. J Am Geriatr Soc. 2017;65(9):1932-1938.
48. Hasemann W, Tolson D, Godwin J, Spirig R, Frei IA, Kressig RW. Nurses’ recognition of hospitalized older patients with delirium and cognitive impairment using the Delirium Obser- vation Screening Scale: a prospective comparison study. J Gerontol Nurs. 2018;44(12):35-43.
49. Marino M, Li Y, Rueschman MN, et al. Measuring sleep: accu- racy, sensitivity, and specificity of wrist actigraphy compared to polysomnography. Sleep. 2013;36(11):1747-1755.
50. Ehlenbach WJ, Hough CL, Crane PK, et al. Association between acute care and critical illness hospitalization and cognitive function in older adults. JAMA. 2010;303(8):763-770.
51. Schulte PJ, Warner DO, Martin DP, et al. Association between critical care admissions and cognitive trajectories in older adults. Crit Care Med. 2019;47(8):1116-1124.
52. Royall DR, Lauterbach EC, Kaufer D, Malloy P, Coburn KL, Black KJ. The cognitive correlates of functional status: a review from the Committee on Research of the American Neuropsychiatric Association. J Neuropsychiatry Clin Neu- rosci. 2007;19(3):249-265.
53. Harrington MB, Kraft M, Grande LJ, Rudolph JL. Independent association between preoperative cognitive status and dis- charge location after cardiac surgery. Am J Crit Care. 2011; 20(2):129-137.
54. Adogwa O, Elsamadicy AA, Sergesketter A, et al. Independent association between preoperative cognitive status and dis- charge location after surgery: a strategy to reduce resource use after surgery for deformity. World Neurosurg. 2018; 110:e67-e72. doi:10.1016/j.wneu.2017.10.081
55. Culley DJ, Flaherty D, Fahey MC, et al. Poor performance on a preoperative cognitive screening test predicts postop- erative complications in older orthopedic surgical patients. Anesthesiology. 2017;127(5):765-774.
56. Ouchi K, Jambaulikar GD, Hohmann S, et al. Prognosis after emergency department intubation to inform shared decision- making. J Am Geriatr Soc. 2018;66(7):1377-1381.
57. Devlin JW, Skrobik Y, Gélinas C, et al. Clinical practice guide- lines for the prevention and management of pain, agitation/ sedation, delirium, immobility, and sleep disruption in adult patients in the ICU. Crit Care Med. 46(9): e825-e873. doi:10.1097/CCM.0000000000003299
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